91 citations · 116 across the 23 of their papers we have counts for
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Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging
Kwanseok Oh, Jieun Lee, Da-Woon Heo +2
Ultrahigh-field (UHF) magnetic resonance imaging (MRI), i.e., 7T MRI, provides superior anatomical details of internal brain structures owing to its enhanced signal-to-noise ratio…
Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model
Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk
Existing studies on disease diagnostic models focus either on diagnostic model learning for performance improvement or on the visual explanation of a trained diagnostic model. We p…
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis
Eunji Jun, Seungwoo Jeong, Da-Woon Heo +1
Transfer learning has gained attention in medical image analysis due to limited annotated 3D medical datasets for training data-driven deep learning models in the real world. Exist…
Fine-Grained Attention for Weakly Supervised Object Localization
Junghyo Sohn, Eunjin Jeon, Wonsik Jung +2
Although recent advances in deep learning accelerated an improvement in a weakly supervised object localization (WSOL) task, there are still challenges to identify the entire body…
Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision
Kwanseok Oh, Jee Seok Yoon, Heung-Il Suk
There exists an apparent negative correlation between performance and interpretability of deep learning models. In an effort to reduce this negative correlation, we propose a Born…
Deep Recurrent Model for Individualized Prediction of Alzheimer's Disease Progression
Wonsik Jung, Eunji Jun, Heung-Il Suk
Alzheimer's disease (AD) is known as one of the major causes of dementia and is characterized by slow progression over several years, with no treatments or available medicines. In…